Newtonβs method
Let be a differentiable function from to . Newtonβs method consists of starting at an for the equation . Then the function is linearized at by replacing the increment by a linear function of the increment .
Now we can solve the linear equation . Since this is a system of n linear equations in n unknowns, can be likened to the general linear system .
Therefore, if is invertible, then . By renaming to , you can reiterate Newtonβs method to get an . Thus, Newtonβs method states
Thus we get a series of βs that we hope will converge to such that . When we solve an equation of the form , we call the solution a root of the equation. Thus, Newtonβs method is used to find roots of nonlinear equations.
Unfortunately, Newtonβs method does not always converge. There are tests for neighborhoods of βs where Newtonβs method will converge however. One such test is Kantorovitchβs theorem, which combines what is needed into a concise mathematical equation.
Corollary 1: Newtonβs Method in one dimension - The above equation is simplified in one dimension to the well-used
This intuitively cute equation is pretty much the equation of first year calculus. :)
Corollary 2: Finding a square root - So now that you know the equation, you need to know how to use it, as it is an algorithm. The construction of the primary equation, of course is the important part. Letβs see how you do it if you want to find a square root of a number b.
We want to find a number x (x for unknown), such that . You might think βwhy not find a number such that ?β Well, the problem with that approach is that we donβt have a value for , so weβd be right back where we started. However, squaring both sides of the equation to get lets us work with the number we do know, .) Back to . With some manipulation, we see this means that ! Thus we have our scenario.
We can see that thus, and . Now we have all we need to carry out Newtonβs method. By renaming to be , we have
.
The equation on the far right is also known as the divide and average method, for those who have not learned the full Newtonβs method, and just want a fast way to find square roots. Letβs see how this works out to find the square root of a number like 2:
Let
Thus, by Newtonβs method,β¦
All we did was plug in the expressions and where Newtonβs method asks for them. Now we have to pick an . Hmm, since
letβs pick a reasonable number between 1 and 2 like 1.5
Looks like our guess was too high. Letβs see what the next iteration says
getting better =) You can use your calculator to find that
Not bad for only two iterations! Of course, the more you iterate, the more decimal places your will be accurate to. By the way, this is also how your calculator/computer finds square roots!
Geometric Interpretation: Consider an arbitrary function such as . Say you wanted to find a root of this function. You know that in the neighborhood of , there is a root (Maybe you used Kantorovitchβs theorem or tested and saw that the function changed signs in this neighborhood). We want to use our knowledge to find an that is a better approximation to (in this case, closer to it on the x-axis).
So we know that or in another case . What is an efficient algorithm to bridge the gap between and ? Letβs look at a tangent line to the graph.
Note that the line intercepts the x-axis between and , which is exactly what we want. The slope of this tangent line is by definition of the derivative at , and we know one point on the line is , since that is the x-intercept. That is all we need to find the formula of the line, and solve for .
Substituting | ||||
Aesthetic change. Flipped the equation around. | ||||
Newtonβs method! |
Title | Newtonβs method |
Canonical name | NewtonsMethod |
Date of creation | 2013-03-22 11:58:05 |
Last modified on | 2013-03-22 11:58:05 |
Owner | alozano (2414) |
Last modified by | alozano (2414) |
Numerical id | 28 |
Author | alozano (2414) |
Entry type | Algorithm |
Classification | msc 49M15 |
Synonym | Newton-Raphson method |
Related topic | LipschitzCondition |
Related topic | KantorovitchsTheorem |
Related topic | Derivative |
Related topic | Superconvergence |
Related topic | FixedPointsOfNormalFunctions |